EP2201493A2 - Tomosynthèse de sein avec affichage de calcifications suspectées mises en évidence - Google Patents

Tomosynthèse de sein avec affichage de calcifications suspectées mises en évidence

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Publication number
EP2201493A2
EP2201493A2 EP08798945A EP08798945A EP2201493A2 EP 2201493 A2 EP2201493 A2 EP 2201493A2 EP 08798945 A EP08798945 A EP 08798945A EP 08798945 A EP08798945 A EP 08798945A EP 2201493 A2 EP2201493 A2 EP 2201493A2
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EP
European Patent Office
Prior art keywords
images
breast
pixels
displaying
calcifications
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Granted
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EP08798945A
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German (de)
English (en)
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EP2201493A4 (fr
EP2201493B1 (fr
Inventor
Chris Ruth
Jay Stein
Loren Niklason
Andrew Smith
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Hologic Inc
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Hologic Inc
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Priority to EP22184413.7A priority Critical patent/EP4123590A3/fr
Publication of EP2201493A2 publication Critical patent/EP2201493A2/fr
Publication of EP2201493A4 publication Critical patent/EP2201493A4/fr
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Publication of EP2201493B1 publication Critical patent/EP2201493B1/fr
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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/025—Tomosynthesis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/12—Arrangements for detecting or locating foreign bodies
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/46—Arrangements for interfacing with the operator or the patient
    • A61B6/461—Displaying means of special interest
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
    • A61B6/502—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of breast, i.e. mammography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/457—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by analysing connectivity, e.g. edge linking, connected component analysis or slices
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5223—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data generating planar views from image data, e.g. extracting a coronal view from a 3D image
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5252—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data removing objects from field of view, e.g. removing patient table from a CT image
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30068—Mammography; Breast
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images
    • G06V2201/032—Recognition of patterns in medical or anatomical images of protuberances, polyps nodules, etc.

Definitions

  • This patent specification pertains to x-ray tomosynthesis, and more specifically to techniques and equipment for acquiring, processing, storing and displaying tomosynthesis images, including tomosynthesis projection images and tomosynthesis reconstructed images.
  • An important aspect of this patent specification pertains to identifying and highlighting suspected calcifications in displays of tomosynthesis images.
  • X-ray mammography remains a well-established technology, and x-ray tomosynthesis of the breast has been developed recently as discussed in the earlier- filed patent applications identified above.
  • Clinical testing of tomosynthesis systems has been carried out, and the assignee of this patent specification, Hologic, Inc., has demonstrated at trade shows in this country a fused, multimode mammography/tomosynthesis system that takes either or both types of images, either in single or multiple compressions/immobilizations of the breast.
  • Dedicated breast tomosynthesis systems also have been proposed.
  • Tomosynthesis as used in the systems and methods disclosed in this patent specification typically involves acquiring a plurality of tomosynthesis projection images Tp at respective angles relative to the breast, and using information describing at least these images Tp (or some of the Tp images) to reconstruct a plurality of tomosynthesis reconstructed images Tr representative of respective breast slices that have selective thicknesses and orientations and correspond to respective sections through or slices of the breast that typically are but need not be planar.
  • the slices can be curved in 3D space.
  • conventional x-ray mammography images Mp can be acquired, in the same procedure that acquires the Tp images of a breast or in a different procedure and in the same or different compressions of the breast, and may be used in addition to the Tp images or in place of some of the Tp images, in reconstructing Tr images.
  • Mp images can be processed by various techniques that draw attention to selected portions or features of these images, such as CAD (computer aided detection) techniques that analyze the images to identify likely abnormalities and place markers on a breast image or representation that identify the location and in some cases the type or other information about the likely abnormalities.
  • CAD computer aided detection
  • Some of the parent applications identified above describe applying CAD analysis to Tr and/or Tp images as well, or as an alternative or an adjunct to applying CAD to Mp images, and also describe how to improve the presentations of Tp and/or Tr images (collectively referred to here as T images), Mp images, and CAD and/or other information about the images to make the review by health professionals more effective and efficient.
  • CAD application to Mp images also is a well-established technology. See, for example, the mammography CAD products offered by R2 Technology, Inc. of Sunnyvale, CA and Patent Publications US 2002/0097902 and US 2004/0100476 and U.S. Patents Nos. 5,970,164, and 6,630,937.
  • U.S. Patent No. 6,748,044 discusses applying CAD to tomosynthesis images and U.S. Patent No. 7,149,335 discusses detecting microcalcifications in tomosynthesis images and subtracting background to enhance visibility of the detected microcalcifications.
  • Also possibly relevant to state-of-the-art may be US20030194121A1, US6748044, US20030215120A1, US20050002550A1, US20060269114A1, US20050089205A1, US200501 13961A1, US7142633, US20060067473A1, US20060210131Al, US200700031 17Al, US20070003118Al, US20070014448Al, US20070052700A1, US20070076928A1.
  • the patents and publication identified in this paragraph also are incorporated by reference in this patent specification. .
  • the notation Mp refers to a conventional mammogram, which is a two-dimensional x-ray projection image of a breast; the term Mp encompasses both a digital image as acquired by a flat panel detector or another imaging device and the image after conventional processing to prepare it for display to a health professional or for further processing or for storage, e.g. in the PACS system of a hospital or another institution. Mp also encompasses digitized film/screen mammograms.
  • Tr refers to an image that is similarly two-dimensional but is taken at a respective tomosynthesis angle between the breast and the origin of the imaging X-rays (typically the focal spot of an X-ray tube), and also encompasses the image as acquired as well as the image after being processed for display or for some other use.
  • Tr refers to an image that is reconstructed from images Tp, for example in the manner described in said earlier-filed patent applications, and represents a slice of the breast essentially as it would appear in a projection X-ray image of that slice at any desired angle, not only at an angle used for Tp or Mp images.
  • a Tr image can represent a slice that conforms to any desired surface such as a flat or curved plane.
  • Tr images can use Mp images in addition to using Tp images or instead of one or more Tp images.
  • Tp, Tr and Mp also encompasses information, in whatever form, that is sufficient to describe such an image for display, further processing, or storage.
  • the images Mp, Tp and Tr typically are in digital form before being displayed, and can be defined by information identifying properties of each pixel in a two-dimensional array of pixels, although other ways to describe the images can be used as well or instead.
  • the pixel values typically relate to respective measured or estimated or computed responses to X-rays of corresponding volumes in the breast (voxels or columns of tissue).
  • a Tr image can represents a thin slice of a breast, in which case it may consist of pixel values representing respective voxels (volume elements) of the breast that are in a single layer or a few layers transverse to the direction of the x-ray beam, or a Tr image may represent a thicker slice of the breast, in which case the pixel values of the thick-slice Tr image can represent columns of tissue along the direction of the x-ray beam and are calculated using known techniques such as, without limitation, a normalized projection of the pixels of several contiguous thin-slice images onto an image plane, a MIP (maximum intensity projection), or some other way of combining the pixel values representing several thin-slice images.
  • MIP maximum intensity projection
  • a thin-slice Tr image can represent a 1 mm thick slice of the imaged breast and a thick-slice Tr image can represent a 5-20 mm thick slice of the breast.
  • a thin-slice Tr image can represent a 1 mm thick slice of the imaged breast and a thick-slice Tr image can represent a 5-20 mm thick slice of the breast.
  • Microcalcifications seen in breast images are considered important clues in screening and/or diagnosis, and prior proposals have been directed to identifying particular specific patterns of microcalcifications or all microcalcifications, or at least those having specified characteristics such as size or density.
  • This patent specification takes a different approach by not only necessarily seeking to identify and classify patterns of microcalcification distributions in images, or to identify or enhance all microcalcifications detectable in the image, but rather to facilitate the visualization of up to a certain number of selected suspected calcifications that meet various special thresholds in a given image or volume of tissue in ways that are particularly useful to the health professional.
  • Calcifications often have a typical x-ray absorption characteristic, but not all objects with these absorption characteristics are calcifications or are of clinical value.
  • Calcifications of clinical interest generally fall in a certain range of sizes and shapes and patterns.
  • the largest calcifications are often benign. Linear ones also are often benign. Identifying all of the very smallest calcification-like objects runs the risk that some of them might represent noise and not true calcifications or reasonably suspected calcifications.
  • One object of the approach disclosed in this patent specification is to reduce the number of identified possible or suspected calcifications which are of lower clinical value.
  • the approach disclosed in this patent specification involves examining through computer processing the individual Tr images in a 3D set of such images to identify an initial set of possible calcifications that meets a threshold limiting the number of identified calcifications in a given Tr image, or in the entire 3D set or a selected subset of the entire 3D set, to a specified number of calcifications and/or number of pixels that are determined to correspond to calcifications.
  • the Tr images are presented for this examination after filtering with a mask that enhances high spatial frequency image features.
  • the process removes from the initial set, pixels initially determined to relate to calcifications that are too large in area or too long in linear extent, and may additionally impose other constraints such as excluding initially determined calcifications that are not present in two adjacent Tr images, applying ligament removal and edge removal techniques, requiring at least a certain number of calcifications to be in a specified volume of the 3D set, and excluding calcifications that are in the initial and trailing Tr images in a stack of Tr images and thus are likely to be at the skin level and unlikely to have clinical significance.
  • the removal processes are designed to remove calcifications that are likely to be devoid of clinical interest and to remove noise and other non-calcification objects.
  • one example is to show a scout view that generally conforms in shape to a projection of the breast and shows a distribution of identified calcifications as well as a current level that both (1) includes calcifications and (2) corresponds to a Tr image that is orthogonal to the scout image and is seen at a main image display.
  • this information can be displayed using a ruler or other schematic display that does not conform in shape to a projection of the breast but still allows display of the current level and/or the locations of likely calcifications.
  • the current level in the 2D scout or schematic view points to one or more corresponding Tr images.
  • the scout or schematic view also shows a pointer to a next level that contains identified calcifications so that a user can conveniently click on that level and thus call on the main display the next Tr image of interest.
  • the scout or schematic view may also indicate how many calcification clusters are in a given Tr image.
  • the user can toggle the main display between showing a Tr image with or without highlighted calcifications therein.
  • a health professional thus can quickly and effectively review Tr images that are likely to be of interest.
  • the health professional can additionally select for the main display additional Tr images, Tr images that are for thick or thin slices and/or reconstructed in another orientation, Tp images and/or Mp images.
  • An alternative or additional process is to initially search Tp and/or Mp images rather than the 3D set of Tr images to identify likely calcifications of interest. This can be done using CAD as disclosed in the patent literature incorporated by reference in this patent specification, or by adapting the principles discussed above for identifying calcifications in Tr images and 3D volumes, or in some other manner. After likely calcifications of clinical significance are identified in the 2D Tp and/or Mp images, the 2D images can be displayed one at a time or several at a time, or only those 2D images that have identified calcifications can be displayed.
  • Tr images of the breast can be searched through the Tr images of the breast to identify and display the Tr image or Tr images that contain that calcification.
  • This search through the Tr images can use knowledge about the location of the likely calcification in the 2D image, on parameters of the calcification such as its size, shape, pixel values and distribution of those values in the 2D image, and possibly other parameters.
  • Tr images In case of an ambiguity, i.e., the calcification pointed to in the 2D image appears in two or more Tr images, all possibly relevant Tr images can be displayed to the user, singly or in a set or subsets or in cine mode, and the user may select for further use the ones that appear relevant or dismiss any that are not.
  • This alternative can reduce processing time because the search for likely calcifications in the 2D images can be faster, and the subsequent search for the Tr slice(s) that contain a calcification to which the user pointed in a 2D image also can be faster.
  • One reason for greater computational efficiency is that the 3D data set (the Tr images) need to be processed only after a likely calcification has been selected, so only a relatively small volume of the 3D set would need to be searched.
  • Another advantage of this alternative may be if the search process is more sensitive and/or more accurate for 2D images. If so, then it is more likely to decrease the overall rate of false negatives and/or false positives in identifying likely calcifications, and thus improve the presentation of images to the health professional and make the overall process of assessing the images for screening, diagnosis, or other purposes, more effective and/or more efficient.
  • the user can point to any feature in one of the 2D images, not necessarily a likely calcification, even in 2D images that have not been processed to identify likely calcifications, and the process can attempt to identify and display for the user the Tr slice(s) in which that feature can be seen well, e.g., the feature is in best focus.
  • the search through the 3D set of pixel data can use information about the feature to which the user pointed, such as location in the 2D image, size, shape, pixel values and distribution of those values, and possibly other parameters. If the feature is relatively unique and small, the process may correctly identify and display for the user one or only a few Tr slices.
  • the process may similarly display the possibly pertinent Tr slices, or may display only those that meet a threshold of relevance, e.g., based on a calculation of their degree of relevance to the feature to which the user pointed.
  • Fig. 1 illustrates an example of a display of a scout image and a reconstructed tomosynthesis slice image Tr.
  • Fig 2 illustrates in block diagram form a mammography/tomosynthesis system that can be used to acquire breast imaging x-ray data and process and display the data according to preferred embodiments of the approach disclosed in this patent specification.
  • FIG 3 is a flowchart illustrating an embodiment of a new process.
  • Fig 4 illustrates a method of displaying a current slice and locations of calcifications.
  • Fig 5 illustrates a method of identifying calcifications on a tomosynthesis slice image Tr.
  • the image on the left is a scout view 10 that generally conforms to an outline of a patient's breast and contains bright dots indicative of calcifications identified through a process described below.
  • Two facing arrows 12a and 12b at the side of scout image 10 point to a level in the scout image that corresponds to a reconstructed tomosynthesis slice image Tr 12 seen at the right side of Fig. 1.
  • the views of images 10 and 12 are mutually orthogonal. Tr image 12 in this example has highlighted calcifications (seen as white dots) that are more numerous than those seen in scout image 10, for reasons that will become apparent from the disclosure below.
  • Tr image 12 can be displayed without highlighting its suspected calcifications, as a normal Tr image, by a user command such as clicking a mouse button or through some other interface.
  • the Tr image that is displayed as image 12 can be for a thin slice, e.g., a 1 mm or somewhat thinner or thicker slice of breast tissue, or for a thick slice such as a 3 mm or somewhat thinner or thicker slice of breast tissue, in which case the thick-slice image can be formed by combining several thin slice Tr image through a known process such as, without limitation, adding with or without normalization, MIP projection, etc.
  • data representing Tp images can be reconstructed into data representing thick-slice Tr images in the reconstruction process using known techniques such as using appropriate backprojection or frequency domain filters.
  • the user can click on button 13a, 13b and 13c to toggle display 12 between a Tr image with and without highlighted suspected calcification, or to the previous and next Tr images.
  • Figure 4 shows an alternative method to the scout view for identifying slice locations for calcifications. This involves a ruler that indicates both the currently- displayed slice, in terms of its height or position in a stack of Tr images and corresponding slices of breast tissue (using a marker such as the one labeled "Slice position indicator” in Fig. 4), and also Calcification slice indicator marks that show the slices where potential calcifications have been identified (by marks such as the arrows labeled "Calcification slice indicator" in Fig. 4).
  • Figure 5 shows an alternative method for identifying calcifications that does not require highlighting them.
  • potential calcifications are outlined by a box such as the one labeled "Square indicating calcifications" in Fig. 5.
  • Arrows pointing to the calcifications would be an alternative method, as would other marks and or lines and or color and/or intensity changes on the image in the vicinity of the calcifications.
  • an x-ray data acquisition unit 100 includes an x-ray source 110 imaging a patient's breast 1 12 supported on a breast platform 114.
  • An x-ray imager 116 such as a flat panel, direct conversion imager available from Hologic, Inc. of Bedford, MA, generates projection image data such as data defining images Mp and/or Tp.
  • X-ray source 1 10 is mounted for movement around breast platform 1 14 so that images Tp (and Mp, if desired) can be taken at a number of different angles for a specific orientation of breast platform 1 14, such as a generally CC orientation or a generally MLO orientation.
  • X-ray imager 116 can be stationary but preferably it also moves relative to breast platform 114, in a specified synchronous relationship to source 110, preferably in a manner that keeps the imaging plane at the same angle to the imaging x-ray beam.
  • Units 110 and 116 communicate with x-ray data acquisition control 1 18 that controls the operation of the system as known from said material incorporated by reference.
  • X-ray data from imager 116 is delivered to processing and image reconstruction unit 120 that includes one or more programmed digital computers, where data is processed as known into Tp and possibly Mp images and into Tr images and where the process described below is carried out.
  • the resulting information is displayed at image display unit 122.
  • the software for any specific implementation of specific data processing hardware can be written without undue experimentation by a person skilled in the art based on the disclosure of this patent specification. The details of such implementation would depend to a certain extent on factors such as the hardware and operating systems that a particular designer or user would select, and many variations are possible. For the sake of both clarity and conciseness such details that are within the skill of the art once the disclosure herein is available, are not included in this patent specification.
  • the processing carried out by unit 120 typically includes known filtering and preliminary processing of the Tp image data (and any Mp data used in addition to or instead of Tp image data) and reconstruction of thin and/or thick slice Tr image data that defines a 3D set of pixel values.
  • the 3D set is made up of the pixel values representing an x-ray property of respective pixels of each of a number of Tr images, each Tr image representing a respective slice of breast tissue.
  • the Tr images used in steps 1- 4 below represent thin slices of the breast, such as 1 mm slices, but using thicker slice images is not excluded.
  • These pixel values are processed in the following principal steps as a non-limiting preferred example following a filtering of the Tr images individually to suppress low spatial frequency components.
  • any one of a number of known filtering processes can be used, such as a process involving the use of unsharp mask filters.
  • the objective is to include in the final set of calc pixels no more than a selected number N of pixels for the entire 3D set of pixels defining the Tr images.
  • candidate calc pixels can be identified in this step by provisionally identifying as calc pixels the pixels that have pixel values exceeding a provisional threshold level.
  • any pixel that has a value greater than, e.g., 40 can be provisionally classified as a calc pixel in a first iteration.
  • the provisional threshold of 40 is raised, e.g., to 41, and the process is repeated to provisionally classify as candidate calc pixel those having pixel values greater than 41. If the initial iteration yields a total number of calc pixels that is too low (as a non-limiting example, less than 50) the initial threshold is lowered, e.g., to 39, and the process is repeated. These iterations are repeated until the total number of candidate calc pixels is in the desired range, for example and without limitation, in the range of 50 to 150 calc pixels for the given Tr image.
  • the specific initial threshold, the size of the steps by which it is raised or lowered, and the desired range of total number of candidate calc pixels can be set depending on user preferences, either as part of the design process or as a parameter that can be set by service personnel or by the user of the system in the field, or on the basis of a study of typical values for a large population of breast images.
  • This step yields a first provisional set of calc pixels.
  • a second provisional set of candidate pixels by excluding those associated with large areas in a Tr image that contain contiguous, i.e., connected, or nearly contiguous candidate calc pixels.
  • the test can be for an area of only contiguous pixels provisionally identified as calc pixels, or it can be for areas in which any provisionally identified calc pixel is spaced by no more than one (or a set multiple of) pixels that are not calc pixels.
  • a third provisional set of calc pixels by removing from the second provisional set the pixels that are generally arranged in lines that have excessive lengths.
  • These linear groups of candidate calc pixels may be associated with blood vessels or other structures that may be of less interest than other calcifications. For example, a line of contiguous or nearly contiguous candidate calc pixels that is more than 2-4 mm long may be considered too long in this step.
  • the term nearly contiguous is used in this patent specification to denote calc pixels that might be separated by one (or a set multiple of) non-calc pixels.
  • each set of three contiguous Tr images into a respective thick-slice Tr image by forming a new pixel by adding the values of three contiguous pixels in a direction transverse to the planes of the Tr images and dividing the result by three.
  • combine into a thick-slice Tr image the several Tr images that contain candidate calc pixels forming in 3D a clump of candidate calc pixels, e.g., a 3D clump of candidate calc pixels that have at least a specified density (ratio of all pixels to candidate calc pixels, or the reverse).
  • Form a fifth set of candidate calc pixels by removing from the fourth set the candidate calc pixels that are arranged in lines that are too long in any direction (e.g. more than 2-4 mm) in a thick-slice Tr image and, therefore, are likely to be associated with structures such as ligaments, blood vessels, or cyst walls.
  • Form a sixth set of candidate calc pixels by eliminating from the fifth set the candidate calc pixels that are not in a set of at least a specified number of candidate calc pixels in a specified volume of the 3D set of pixels, e.g., in a volume that represents a 1 cm by 1 cm by 3 mm volume of the breast, where the 3 mm is the size of the thick slice Tr image.
  • a seventh set of candidate calc pixels by eliminating from the sixth set the candidate calc pixels that are too low in density in the 3D volume of pixels. For example, eliminate candidate calc pixels that are in a volume of the 3D set of pixels of a specified size in which there is too low a ratio of (a) total number of calc pixels in the volume to (b) the number of candidate calcs, where a candidate calc consists of connected calc pixels. As a non-limiting example, a ratio less than 1.1 in a volume of 1 cm by 1 cm by 3 mm can be considered too low. This step tends to eliminate candidate calcs that may represent image noise.
  • enhance the projected calc pixels so that they would stand out better in image 10. For example, increase the pixel values of the calc pixels in the final set to a higher value so that they appear as brighter spots in the scout image and/or increase the sizes of spots in the scout image that represent determined calcifications by setting to a higher or highest pixel value the pixels that are within a specified distance from a calc pixel that is in the final set.
  • arrows in the scout images 10 and Tr images 12 for display as in Fig. 1, for example by including in display unit 122 appropriate user interface devices such as a mouse or other pointer to enable the user to click on selected arrows in image 10 and to make the system respond to the clicks as described above[cu .
  • appropriate user interface devices such as a mouse or other pointer to enable the user to click on selected arrows in image 10 and to make the system respond to the clicks as described above[cu .
  • a thin-slice Tr image can represent a 1 mm thick slice of breast tissue while a thick-slice Tr image can represent a 3 mm or thicker slice of breast tissueMj .
  • slabbing Provide for user interaction in selecting display of images 12 with or without such enhancement by higher brightness of pixels representing calcifications in images 12, by slabbing a given number of slices to form a thick slice.
  • the calc pixels may be slabbed independently of the image pixels that are not identified as calc pixels.
  • the term "slabbing" is used here in the sense of "combining” or "integrating" parameters of the pixels of images representing thinner slices into pixels of an image representing a thicker slice.
  • slabbing techniques can be used such as averaging with or without normality after, median, mode, maximum, MIP and/or other operations for collapsing columns of pixels.
  • Fig. 3 illustrates a particular implementation of a process related to the above-described example.
  • the process of Fig. 3 starts with inputting data describing the reconstructed images Tr for a given view, e.g., the Tr images reconstructed from the Tp images taken when the breast is imaged in a position suitable for a CC or an MLO view.
  • the numbered steps discussed below correspond to the blocks of Fig. 3.
  • the input Tr images are reconstructed images representing breast tissue slices, where the pixel values outside the breast area are constant (i.e., the image has been masked by previous processing).
  • global parameters are defined, and adjusted for pixel size, and memory is allocated to process the given Mammographic View; which in this case is a Tr image.
  • a global threshold is defined using a specified slice, for example, the center slice in the stack (View) as follows.
  • the resultant threshold is used for all subsequent slices. Note that the method for calculating threshold can also be used for each slice separately.
  • Nmax MaxPixArea/PixSize 2
  • PixSize size of pixels in mm
  • MaxPixArea 0.3mm 2
  • Range Cut a Calculate the linear extent of labels in x and y b. Delete labels that have an extent (in either direction) larger than 0.63mm
  • Boundary Cut a Delete labels that are close to the breast boundary. Currently, if a label pixel is within 3mm of the skin edge, it is deleted.
  • the candidate image K is 'slabbed' (as a non-limiting example, added on a per pixel basis) with adjacent slices to give binary Slab image Sj.
  • the slabbing is per pixel and uses 3 contiguous slices.
  • a running sum may be used for efficiency if the Tr slice images are input consecutively.
  • the first slice of the previous slab is subtracted and the current slice is added to the slab image.
  • Sj is then Re-labeled to give new label image Mj.
  • N g ⁇ k ( f x ⁇ l, if V j > V j+k 0, if V j ⁇ V j+k ⁇
  • Nx number of columns in the image.
  • CPD (Number of pixels in group) ⁇ (Number of labels (calcs) in group)
  • Ave(C) average pixel value of labels in the group.
  • Ave(N) average pixel value of neighboring pixels (nearest neighbors of C) In the average calculations only labels that have less than 3 pixels are considered. If the number of labels used in the average is greater than 0.6 x (total number of labels in group), apply the following cuts.
  • Nchi chi-squared ⁇ Number of points used in fit
  • Regroup the valid labels in the volume such that labeled pixels that are within ⁇ lOmm in x,y, and ⁇ 5mm in z, are in the same group. This connects groups that may exist over several slices and may contain a slice with no labeled pixels. This step combines the previous per slice groups that may overlap (or be close) in the volume.
  • SOI's are those slices which may be used in the Viewing application that will allow the user to quickly scroll the TCE identified slices within a View.
  • a SOI is defined for each identified group as the slice that contains the most labeled pixels in that group. Note that 2 different groups may have the same SOI.
  • the display of a given slice might contain calcifications (or masses) from other slices, especially if they have been ascertained to be part of the same cluster. If desired, a different highlighting can be applied to calcs or masses that also are present in adjacent Tr slices that are not displayed at the moment.
  • breast slice images that include pixels determined to be calcifications
  • the user can be helped to identify the calc pixels, particularly if their brightness is enhanced as discussed above, by the sudden change in brightness in scrolling from one displayed slice image to the next or help can be provided by marking the calc, e.g. with some symbol.
  • The[c7j change from one slice image to another can be directed manually by the user, or the display can be automated to present the succession of slice images in cine format.
  • the process can be adapted to identify masses using for example CAD techniques such as those described in the material incorporated in this patent specification by reference. Suspected abnormalities can then be selectively specified to be (1) only calcifications, (2) only masses, and (3) both calcifications and masses. The selection and display of masses can then be similar to the selection and display of calcifications described above.
  • a simpler process can be used such as a filter that identifies all pixels in a Tp and/or Tr image that meet specified threshold criteria of pixel values selected to identify pixels likely to correspond to calcifications.
  • Known techniques can be used to eliminate from an initial cut those abnormalities that are likely to represent noise, such as isolated single pixels that meet the threshold criteria or very small groups of such pixels. The remaining suspected abnormalities can then be displayed as described above.
  • An alternative or additional process involves finding likely calcification in the individual 2D Tp and/or Mp images and then searching only subsets of the 3D Tr images to select corresponding Tr images for selective display to the user. This can be implemented by initially searching Tp and/or Mp images rather than the 3D set of Tr images to identify likely calcifications of interest.
  • the initial search of 2D images can be done using CAD as disclosed in the patent literature incorporated by reference in this patent specification, or by adapting the principles discussed above for identifying calcifications in Tr images and 3D volumes, or in some other manner.
  • the 2D images can be displayed one at a time or several at a time, or only those 2D images that have identified calcifications can be displayed.
  • computer processing can search through the Tr images of the breast to identify and display the Tr image or Tr images that contain that calcification. This search through the Tr images can use knowledge about the location of the likely calcification in the 2D image, on parameters of the calcification such as its size, shape, pixel values and distribution of those values in the 2D image, and possibly other parameters.
  • Tr images In case of an ambiguity, i.e., the calcification pointed to in the 2D image appears in two or more Tr images, all possibly relevant Tr images can be displayed to the user, singly or in a set or subsets or in cine mode, and the user may select for further use the ones that appear relevant or dismiss any that are not.
  • This alternative can reduce processing time because the search for likely calcifications in the 2D images can be faster, and the subsequent search for the Tr slice(s) that contain a calcification to which the user pointed in a 2D image also can be faster.
  • One reason for greater computational efficiency is that the 3D data set (the Tr images) need to be processed only after a likely calcification has been selected, so only a relatively small volume of the 3D set would need to be searched.
  • Another advantage of this alternative may be if the search process is more sensitive and/or more accurate for 2D images. If so, then it is more likely to decrease the overall rate of false negatives and/or false positives in identifying likely calcifications, and thus improve the presentation of images to the health professional and make the overall process of assessing the images for screening, diagnosis, or other purposes, more effective and/or more efficient.
  • the user can point to any feature in one of the 2D images, not necessarily a likely calcification, even in 2D images that have not been processed to identify likely calcifications, and the process can attempt to identify and display for the user the Tr slice(s) in which that feature can be seen well, e.g., the feature is in best focus.
  • the search through the 3D set of pixel data can use information about the feature to which the user pointed, such as location in the 2D image, size, shape, pixel values and distribution of those values, and possibly other parameters. If the feature is relatively unique and small, the process may correctly identify and display for the user one or only a few Tr slices.
  • the process may similarly display the possibly pertinent Tr slices, or may display only those that meet a threshold of relevance, e.g., based on a calculation of their degree of relevance to the feature to which the user pointed.

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Abstract

La présente invention concerne des systèmes et des procédés qui facilitent la présentation et l'évaluation de caractéristiques sélectionnées dans des images de projection et/ou de reconstruction de sein, telles que des calcifications qui répondent aux critères sélectionnés de taille, forme, présence dans des images en coupe sélectionnées, distribution de pixels susceptibles d'être révélateurs d'une calcification relativement à d'autres pixels ou d'autres caractéristiques d'image d'intérêt clinique.
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US9202275B2 (en) 2015-12-01
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EP4123590A3 (fr) 2023-03-29
EP4123590A2 (fr) 2023-01-25
US7630533B2 (en) 2009-12-08
US20140112563A1 (en) 2014-04-24
US20100086188A1 (en) 2010-04-08
US20150049934A1 (en) 2015-02-19
US20120121155A1 (en) 2012-05-17
WO2009038948A2 (fr) 2009-03-26
US20090080752A1 (en) 2009-03-26
US8131049B2 (en) 2012-03-06
US8873824B2 (en) 2014-10-28
EP2201493B1 (fr) 2022-07-13

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